DocumentCode :
507334
Title :
A Fast Segmentation Method Based on Curve Evolution Model and Edgeflow
Author :
Xie Qing-Song ; Li Jin-jiang ; Yuan Da
Author_Institution :
Sch. of Comput. Sci. & Technol., Shandong Inst. of Bus. & Technol., Yantai, China
Volume :
5
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
307
Lastpage :
310
Abstract :
This paper proposes a high-accuracy edge contour extraction algorithm based on curve evolution model and edgeflow. The approach automatically detect boundaries, and change of topology in terms of the edgeflow fields. We present the numerical implementation and the experimental results based on the semi-implicit method. Experimental results are given to demonstrate the feasibility of the proposed method in extracting contour from the blurred edge and high-noise images.
Keywords :
edge detection; image segmentation; blurred edge; curve evolution model; edgeflow; fast segmentation method; high-accuracy edge contour extraction; high-noise images; semi-implicit method; Change detection algorithms; Computer science; Deconvolution; Filtering; Filters; Fuzzy systems; Image edge detection; Iterative methods; Partial differential equations; Topology; Curve Evolution; Edgeflow; Segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
Type :
conf
DOI :
10.1109/FSKD.2009.80
Filename :
5360611
Link To Document :
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